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FEAT: NEW WORKFLOW ENGINE (#3160)

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Co-authored-by: Joel <iamjoel007@gmail.com>
Co-authored-by: Yeuoly <admin@srmxy.cn>
Co-authored-by: JzoNg <jzongcode@gmail.com>
Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
Co-authored-by: jyong <jyong@dify.ai>
Co-authored-by: nite-knite <nkCoding@gmail.com>
Co-authored-by: jyong <718720800@qq.com>
This commit is contained in:
takatost
2024-04-08 18:51:46 +08:00
committed by GitHub
parent 2fb9850af5
commit 7753ba2d37
1161 changed files with 103836 additions and 10327 deletions
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0
api/tests/unit_tests/core/prompt/__init__.py Normal file
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api/tests/unit_tests/core/prompt/test_advanced_prompt_transform.py Normal file
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from unittest.mock import MagicMock
import pytest
from core.app.app_config.entities import ModelConfigEntity, FileExtraConfig
from core.file.file_obj import FileVar, FileType, FileTransferMethod
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_runtime.entities.message_entities import UserPromptMessage, AssistantPromptMessage, PromptMessageRole
from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
from core.prompt.entities.advanced_prompt_entities import CompletionModelPromptTemplate, MemoryConfig, ChatModelMessage
from core.prompt.utils.prompt_template_parser import PromptTemplateParser
from models.model import Conversation
def test__get_completion_model_prompt_messages():
model_config_mock = MagicMock(spec=ModelConfigEntity)
model_config_mock.provider = 'openai'
model_config_mock.model = 'gpt-3.5-turbo-instruct'
prompt_template = "Context:\n{{#context#}}\n\nHistories:\n{{#histories#}}\n\nyou are {{name}}."
prompt_template_config = CompletionModelPromptTemplate(
text=prompt_template
)
memory_config = MemoryConfig(
role_prefix=MemoryConfig.RolePrefix(
user="Human",
assistant="Assistant"
),
window=MemoryConfig.WindowConfig(
enabled=False
)
)
inputs = {
"name": "John"
}
files = []
context = "I am superman."
memory = TokenBufferMemory(
conversation=Conversation(),
model_instance=model_config_mock
)
history_prompt_messages = [
UserPromptMessage(content="Hi"),
AssistantPromptMessage(content="Hello")
]
memory.get_history_prompt_messages = MagicMock(return_value=history_prompt_messages)
prompt_transform = AdvancedPromptTransform()
prompt_transform._calculate_rest_token = MagicMock(return_value=2000)
prompt_messages = prompt_transform._get_completion_model_prompt_messages(
prompt_template=prompt_template_config,
inputs=inputs,
query=None,
files=files,
context=context,
memory_config=memory_config,
memory=memory,
model_config=model_config_mock
)
assert len(prompt_messages) == 1
assert prompt_messages[0].content == PromptTemplateParser(template=prompt_template).format({
"#context#": context,
"#histories#": "\n".join([f"{'Human' if prompt.role.value == 'user' else 'Assistant'}: "
f"{prompt.content}" for prompt in history_prompt_messages]),
**inputs,
})
def test__get_chat_model_prompt_messages(get_chat_model_args):
model_config_mock, memory_config, messages, inputs, context = get_chat_model_args
files = []
query = "Hi2."
memory = TokenBufferMemory(
conversation=Conversation(),
model_instance=model_config_mock
)
history_prompt_messages = [
UserPromptMessage(content="Hi1."),
AssistantPromptMessage(content="Hello1!")
]
memory.get_history_prompt_messages = MagicMock(return_value=history_prompt_messages)
prompt_transform = AdvancedPromptTransform()
prompt_transform._calculate_rest_token = MagicMock(return_value=2000)
prompt_messages = prompt_transform._get_chat_model_prompt_messages(
prompt_template=messages,
inputs=inputs,
query=query,
files=files,
context=context,
memory_config=memory_config,
memory=memory,
model_config=model_config_mock
)
assert len(prompt_messages) == 6
assert prompt_messages[0].role == PromptMessageRole.SYSTEM
assert prompt_messages[0].content == PromptTemplateParser(
template=messages[0].text
).format({**inputs, "#context#": context})
assert prompt_messages[5].content == query
def test__get_chat_model_prompt_messages_no_memory(get_chat_model_args):
model_config_mock, _, messages, inputs, context = get_chat_model_args
files = []
prompt_transform = AdvancedPromptTransform()
prompt_transform._calculate_rest_token = MagicMock(return_value=2000)
prompt_messages = prompt_transform._get_chat_model_prompt_messages(
prompt_template=messages,
inputs=inputs,
query=None,
files=files,
context=context,
memory_config=None,
memory=None,
model_config=model_config_mock
)
assert len(prompt_messages) == 3
assert prompt_messages[0].role == PromptMessageRole.SYSTEM
assert prompt_messages[0].content == PromptTemplateParser(
template=messages[0].text
).format({**inputs, "#context#": context})
def test__get_chat_model_prompt_messages_with_files_no_memory(get_chat_model_args):
model_config_mock, _, messages, inputs, context = get_chat_model_args
files = [
FileVar(
id="file1",
tenant_id="tenant1",
type=FileType.IMAGE,
transfer_method=FileTransferMethod.REMOTE_URL,
url="https://example.com/image1.jpg",
extra_config=FileExtraConfig(
image_config={
"detail": "high",
}
)
)
]
prompt_transform = AdvancedPromptTransform()
prompt_transform._calculate_rest_token = MagicMock(return_value=2000)
prompt_messages = prompt_transform._get_chat_model_prompt_messages(
prompt_template=messages,
inputs=inputs,
query=None,
files=files,
context=context,
memory_config=None,
memory=None,
model_config=model_config_mock
)
assert len(prompt_messages) == 4
assert prompt_messages[0].role == PromptMessageRole.SYSTEM
assert prompt_messages[0].content == PromptTemplateParser(
template=messages[0].text
).format({**inputs, "#context#": context})
assert isinstance(prompt_messages[3].content, list)
assert len(prompt_messages[3].content) == 2
assert prompt_messages[3].content[1].data == files[0].url
@pytest.fixture
def get_chat_model_args():
model_config_mock = MagicMock(spec=ModelConfigEntity)
model_config_mock.provider = 'openai'
model_config_mock.model = 'gpt-4'
memory_config = MemoryConfig(
window=MemoryConfig.WindowConfig(
enabled=False
)
)
prompt_messages = [
ChatModelMessage(
text="You are a helpful assistant named {{name}}.\n\nContext:\n{{#context#}}",
role=PromptMessageRole.SYSTEM
),
ChatModelMessage(
text="Hi.",
role=PromptMessageRole.USER
),
ChatModelMessage(
text="Hello!",
role=PromptMessageRole.ASSISTANT
)
]
inputs = {
"name": "John"
}
context = "I am superman."
return model_config_mock, memory_config, prompt_messages, inputs, context

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api/tests/unit_tests/core/prompt/test_prompt_transform.py Normal file
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from unittest.mock import MagicMock
from core.app.app_config.entities import ModelConfigEntity
from core.entities.provider_configuration import ProviderModelBundle
from core.model_runtime.entities.message_entities import UserPromptMessage
from core.model_runtime.entities.model_entities import ModelPropertyKey, AIModelEntity, ParameterRule
from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
from core.prompt.prompt_transform import PromptTransform
def test__calculate_rest_token():
model_schema_mock = MagicMock(spec=AIModelEntity)
parameter_rule_mock = MagicMock(spec=ParameterRule)
parameter_rule_mock.name = 'max_tokens'
model_schema_mock.parameter_rules = [
parameter_rule_mock
]
model_schema_mock.model_properties = {
ModelPropertyKey.CONTEXT_SIZE: 62
}
large_language_model_mock = MagicMock(spec=LargeLanguageModel)
large_language_model_mock.get_num_tokens.return_value = 6
provider_model_bundle_mock = MagicMock(spec=ProviderModelBundle)
provider_model_bundle_mock.model_type_instance = large_language_model_mock
model_config_mock = MagicMock(spec=ModelConfigEntity)
model_config_mock.model = 'gpt-4'
model_config_mock.credentials = {}
model_config_mock.parameters = {
'max_tokens': 50
}
model_config_mock.model_schema = model_schema_mock
model_config_mock.provider_model_bundle = provider_model_bundle_mock
prompt_transform = PromptTransform()
prompt_messages = [UserPromptMessage(content="Hello, how are you?")]
rest_tokens = prompt_transform._calculate_rest_token(prompt_messages, model_config_mock)
# Validate based on the mock configuration and expected logic
expected_rest_tokens = (model_schema_mock.model_properties[ModelPropertyKey.CONTEXT_SIZE]
- model_config_mock.parameters['max_tokens']
- large_language_model_mock.get_num_tokens.return_value)
assert rest_tokens == expected_rest_tokens
assert rest_tokens == 6

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api/tests/unit_tests/core/prompt/test_simple_prompt_transform.py Normal file
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from unittest.mock import MagicMock
from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_runtime.entities.message_entities import UserPromptMessage, AssistantPromptMessage
from core.prompt.simple_prompt_transform import SimplePromptTransform
from models.model import AppMode, Conversation
def test_get_common_chat_app_prompt_template_with_pcqm():
prompt_transform = SimplePromptTransform()
pre_prompt = "You are a helpful assistant."
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.CHAT,
provider="openai",
model="gpt-4",
pre_prompt=pre_prompt,
has_context=True,
query_in_prompt=True,
with_memory_prompt=True,
)
prompt_rules = prompt_template['prompt_rules']
assert prompt_template['prompt_template'].template == (prompt_rules['context_prompt']
+ pre_prompt + '\n'
+ prompt_rules['histories_prompt']
+ prompt_rules['query_prompt'])
assert prompt_template['special_variable_keys'] == ['#context#', '#histories#', '#query#']
def test_get_baichuan_chat_app_prompt_template_with_pcqm():
prompt_transform = SimplePromptTransform()
pre_prompt = "You are a helpful assistant."
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.CHAT,
provider="baichuan",
model="Baichuan2-53B",
pre_prompt=pre_prompt,
has_context=True,
query_in_prompt=True,
with_memory_prompt=True,
)
prompt_rules = prompt_template['prompt_rules']
assert prompt_template['prompt_template'].template == (prompt_rules['context_prompt']
+ pre_prompt + '\n'
+ prompt_rules['histories_prompt']
+ prompt_rules['query_prompt'])
assert prompt_template['special_variable_keys'] == ['#context#', '#histories#', '#query#']
def test_get_common_completion_app_prompt_template_with_pcq():
prompt_transform = SimplePromptTransform()
pre_prompt = "You are a helpful assistant."
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.WORKFLOW,
provider="openai",
model="gpt-4",
pre_prompt=pre_prompt,
has_context=True,
query_in_prompt=True,
with_memory_prompt=False,
)
prompt_rules = prompt_template['prompt_rules']
assert prompt_template['prompt_template'].template == (prompt_rules['context_prompt']
+ pre_prompt + '\n'
+ prompt_rules['query_prompt'])
assert prompt_template['special_variable_keys'] == ['#context#', '#query#']
def test_get_baichuan_completion_app_prompt_template_with_pcq():
prompt_transform = SimplePromptTransform()
pre_prompt = "You are a helpful assistant."
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.WORKFLOW,
provider="baichuan",
model="Baichuan2-53B",
pre_prompt=pre_prompt,
has_context=True,
query_in_prompt=True,
with_memory_prompt=False,
)
print(prompt_template['prompt_template'].template)
prompt_rules = prompt_template['prompt_rules']
assert prompt_template['prompt_template'].template == (prompt_rules['context_prompt']
+ pre_prompt + '\n'
+ prompt_rules['query_prompt'])
assert prompt_template['special_variable_keys'] == ['#context#', '#query#']
def test_get_common_chat_app_prompt_template_with_q():
prompt_transform = SimplePromptTransform()
pre_prompt = ""
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.CHAT,
provider="openai",
model="gpt-4",
pre_prompt=pre_prompt,
has_context=False,
query_in_prompt=True,
with_memory_prompt=False,
)
prompt_rules = prompt_template['prompt_rules']
assert prompt_template['prompt_template'].template == prompt_rules['query_prompt']
assert prompt_template['special_variable_keys'] == ['#query#']
def test_get_common_chat_app_prompt_template_with_cq():
prompt_transform = SimplePromptTransform()
pre_prompt = ""
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.CHAT,
provider="openai",
model="gpt-4",
pre_prompt=pre_prompt,
has_context=True,
query_in_prompt=True,
with_memory_prompt=False,
)
prompt_rules = prompt_template['prompt_rules']
assert prompt_template['prompt_template'].template == (prompt_rules['context_prompt']
+ prompt_rules['query_prompt'])
assert prompt_template['special_variable_keys'] == ['#context#', '#query#']
def test_get_common_chat_app_prompt_template_with_p():
prompt_transform = SimplePromptTransform()
pre_prompt = "you are {{name}}"
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.CHAT,
provider="openai",
model="gpt-4",
pre_prompt=pre_prompt,
has_context=False,
query_in_prompt=False,
with_memory_prompt=False,
)
assert prompt_template['prompt_template'].template == pre_prompt + '\n'
assert prompt_template['custom_variable_keys'] == ['name']
assert prompt_template['special_variable_keys'] == []
def test__get_chat_model_prompt_messages():
model_config_mock = MagicMock(spec=ModelConfigWithCredentialsEntity)
model_config_mock.provider = 'openai'
model_config_mock.model = 'gpt-4'
memory_mock = MagicMock(spec=TokenBufferMemory)
history_prompt_messages = [
UserPromptMessage(content="Hi"),
AssistantPromptMessage(content="Hello")
]
memory_mock.get_history_prompt_messages.return_value = history_prompt_messages
prompt_transform = SimplePromptTransform()
prompt_transform._calculate_rest_token = MagicMock(return_value=2000)
pre_prompt = "You are a helpful assistant {{name}}."
inputs = {
"name": "John"
}
context = "yes or no."
query = "How are you?"
prompt_messages, _ = prompt_transform._get_chat_model_prompt_messages(
app_mode=AppMode.CHAT,
pre_prompt=pre_prompt,
inputs=inputs,
query=query,
files=[],
context=context,
memory=memory_mock,
model_config=model_config_mock
)
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.CHAT,
provider=model_config_mock.provider,
model=model_config_mock.model,
pre_prompt=pre_prompt,
has_context=True,
query_in_prompt=False,
with_memory_prompt=False,
)
full_inputs = {**inputs, '#context#': context}
real_system_prompt = prompt_template['prompt_template'].format(full_inputs)
assert len(prompt_messages) == 4
assert prompt_messages[0].content == real_system_prompt
assert prompt_messages[1].content == history_prompt_messages[0].content
assert prompt_messages[2].content == history_prompt_messages[1].content
assert prompt_messages[3].content == query
def test__get_completion_model_prompt_messages():
model_config_mock = MagicMock(spec=ModelConfigWithCredentialsEntity)
model_config_mock.provider = 'openai'
model_config_mock.model = 'gpt-3.5-turbo-instruct'
memory = TokenBufferMemory(
conversation=Conversation(),
model_instance=model_config_mock
)
history_prompt_messages = [
UserPromptMessage(content="Hi"),
AssistantPromptMessage(content="Hello")
]
memory.get_history_prompt_messages = MagicMock(return_value=history_prompt_messages)
prompt_transform = SimplePromptTransform()
prompt_transform._calculate_rest_token = MagicMock(return_value=2000)
pre_prompt = "You are a helpful assistant {{name}}."
inputs = {
"name": "John"
}
context = "yes or no."
query = "How are you?"
prompt_messages, stops = prompt_transform._get_completion_model_prompt_messages(
app_mode=AppMode.CHAT,
pre_prompt=pre_prompt,
inputs=inputs,
query=query,
files=[],
context=context,
memory=memory,
model_config=model_config_mock
)
prompt_template = prompt_transform.get_prompt_template(
app_mode=AppMode.CHAT,
provider=model_config_mock.provider,
model=model_config_mock.model,
pre_prompt=pre_prompt,
has_context=True,
query_in_prompt=True,
with_memory_prompt=True,
)
prompt_rules = prompt_template['prompt_rules']
full_inputs = {**inputs, '#context#': context, '#query#': query, '#histories#': memory.get_history_prompt_text(
max_token_limit=2000,
ai_prefix=prompt_rules['human_prefix'] if 'human_prefix' in prompt_rules else 'Human',
human_prefix=prompt_rules['assistant_prefix'] if 'assistant_prefix' in prompt_rules else 'Assistant'
)}
real_prompt = prompt_template['prompt_template'].format(full_inputs)
assert len(prompt_messages) == 1
assert stops == prompt_rules.get('stops')
assert prompt_messages[0].content == real_prompt